Glassware crack defects detection based on wavelet transform
| Autor: | Shengnan Xu, Baozhong Tian, Zhenhua Li |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry Wavelet transform Pattern recognition 02 engineering and technology Image segmentation 021001 nanoscience & nanotechnology 01 natural sciences Image (mathematics) 010309 optics Frequency domain 0103 physical sciences Segmentation Artificial intelligence 0210 nano-technology business |
| Zdroj: | 2017 Chinese Automation Congress (CAC). |
| DOI: | 10.1109/cac.2017.8243657 |
| Popis: | An algorithm for detecting and extracting crack defects in glassware using wavelet transform is proposed in this paper. Firstly, the canny image segmentation and the local adaptive dynamic threshold segmentation are carried out on the glassware image with unobvious crack defects. Then, the wavelet decomposition is applied separately on the segmented images. And finally the wavelet fusion is used to extract the crack defects. Experiments show that the proposed algorithm works well in detecting glassware crack defects. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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